Statistical Physics
| Code: | FIS3018 | Acronym: | FIS3018 |
| Keywords | |
|---|---|
| Classification | Keyword |
| OFICIAL | Physics |
Instance: 2023/2024 - 1S 
| Active? | Yes |
| Responsible unit: | Department of Physics and Astronomy |
| Course/CS Responsible: | Bachelor in Engineering Physics |
Cycles of Study/Courses
| Acronym | No. of Students | Study Plan | Curricular Years | Credits UCN | Credits ECTS | Contact hours | Total Time |
|---|---|---|---|---|---|---|---|
| L:B | 0 | Official Study Plan | 3 | - | 6 | 48 | 162 |
| L:CC | 0 | study plan from 2021/22 | 2 | - | 6 | 48 | 162 |
| 3 | |||||||
| L:EF | 92 | study plan from 2021/22 | 3 | - | 6 | 48 | 162 |
| L:F | 50 | Official Study Plan | 3 | - | 6 | 48 | 162 |
| L:G | 4 | study plan from 2017/18 | 2 | - | 6 | 48 | 162 |
| 3 | |||||||
| L:M | 0 | Official Study Plan | 2 | - | 6 | 48 | 162 |
| 3 | |||||||
| L:MA | 0 | Official Study Plan | 3 | - | 6 | 48 | 162 |
| L:Q | 0 | study plan from 2016/17 | 3 | - | 6 | 48 | 162 |
Teaching language
PortugueseObjectives
To get familiar with the ideas and methods of statistical physics. To introduce the fundamental results of classical and quantum statistical physics of systems in equilibrium. To discuss some applications of statistical physics to classical and quantum systems.
Learning outcomes and competences
To be able to solve problems by means of a statistical approach and to establish the connection with thermodynamics. To perform some simple numerical simulations.
Working method
PresencialPre-requirements (prior knowledge) and co-requirements (common knowledge)
Some basic knowledge of Mechanics and Thermal Physics.
Program
Notions of the Theory of Probability and Statistics. Binomial, Gaussian and Poisson distributions. Central limit theorem. Numerical simulation of random processes. Random walk and the diffusion equation. Ideas based on Statistical Physics. Description and enumeration of states. Statistical ensemble. Classical systems. Dynamics in phase space. Ergodic hypothesis. Classical Statistical Physics. Microcanonical, canonical and macrocanonical distributions. Monte-Carlo Method in Statistical Physics. Simple and importance sampling. Metropolis method. Quantum statistics. Bose-Einstein and Fermi-Dirac statistics. Classical limit. Perfect Bose gas. Perfect Fermi gas. Applications. Bose-Einstein condensation, conduction electrons in metals, specific heat of solids, star equilibrium and evolution.
Mandatory literature
Kardar Mehran; Statistical physics of particles. ISBN: 978-0-521-87342-0Reif F. (Frederick); Fundamentals of statistical and thermal physics. ISBN: 0-07-051800-9
T. Fliesbach ; Curso de Física Estatística
S. Salinas ; Introdução à Física Estatística
E. Lage ; Física Estatística
Complementary Bibliography
Huang Kerson; Statistical mechanics. ISBN: 0-471-81518-7Harvey Gould; Thermal and statistical physics simulations. ISBN: 0-471-54886-3
Teaching methods and learning activities
Practical classes to solve analytical and computacional problems.
Software
Pythonkeywords
Physical sciencesEvaluation Type
Distributed evaluation with final examAssessment Components
| designation | Weight (%) |
|---|---|
| Exame | 80,00 |
| Trabalho escrito | 20,00 |
| Total: | 100,00 |
Amount of time allocated to each course unit
| designation | Time (hours) |
|---|---|
| Frequência das aulas | 49,00 |
| Estudo autónomo | 113,00 |
| Total: | 162,00 |
Eligibility for exams
Students should not exceed 4 absences in problem classes.
Calculation formula of final grade
The student must opt for an assessment with a continuous component and
an exam or just to take an exam.
In the assessment with a continuous component, the student must do three
homework during the semester. The continuous component is worth 20% of
the final grade and the exam 80%.
In the evaluation without continuous component, the exam is worth 100%.
Examinations or Special Assignments
The continuous component is made with three homework that must be delivered in 7 days. Each homework counts 6.6666%.Internship work/project
Special assessment (TE, DA, ...)
Classification improvement
Only the exam grade can be improved.Observations
Students who obtain a mark greater or equal to 17 must defend the grade in an additional test.The jury of the curricular unit includes:
João Manuel Viana Parente Lopes
Eduardo Filipe Vieira Castro
Vitor Pereira
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